Let's begin! Staff Software Engineer

Moody's•Newark, NJ

About The Position

Moody’s is seeking a Staff Software Engineer to set the technical direction and long-term roadmap for the Moody’s Insurance Solutions data platform. The role owns the reference architecture and operational standards for a mission-critical, self-hosted Microsoft SQL Server estate running on Linux and Kubernetes in AWS, including availability, performance, recoverability, security, compliance, and cost. It also leads the architecture for data movement from SQL Server into the lakehouse and establishes deployment patterns, schema change management, observability baselines, runbooks, and cost guardrails. The engineer will sequence a 12-to-24-month platform roadmap against business priorities, lead complex technical problems and incidents, mentor and sponsor engineers, and represent the platform in architecture forums and to engineering leadership. The Data Platform Team builds and operates the foundational data services, infrastructure, and tooling that power Moody’s Insurance Solutions products and partners with product engineering teams to support growth and modernization. The anticipated US base salary is $168,100–$243,700, depending on experience, education, level, skills, and location. The role is eligible for incentive compensation. Moody’s offers benefits including medical, dental, and vision coverage, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, discounted employee stock purchase, and tuition reimbursement.

Requirements

At least 8 years of experience in software and data platform engineering, owning a technical domain across multiple teams.
Deep SQL Server expertise and administration, including internals, performance at scale, high availability and disaster recovery architecture, and capacity planning; experience as the final escalation point for SQL Server problems.
Experience designing stateful, data-intensive SQL Server workloads on Linux and Kubernetes using StatefulSets, persistent volumes, and pod quality of service.
Deep AWS experience across Elastic Kubernetes Service, Elastic Compute Cloud, Elastic Block Store, Simple Storage Service, Identity and Access Management, and networking, with the ability to reason about cost and reliability together.
Production lakehouse architecture experience with Apache Iceberg or Delta Lake, including catalog strategy, compaction, and table maintenance.
Experience with replication and change data capture architecture at scale, including failure and recovery modes.
Experience setting estate-wide operational standards, including configuration baselines, patch and cumulative update strategy, and integrity and maintenance regimes.
Database security and compliance architecture experience, including encryption, access control, auditing, and key management.
Ability to influence architecture without authority through RFC documents or standards adopted beyond one’s team.
Strong C#/.NET backend engineering skills, including the ability to write and review production code.
Excellent written communication skills for a distributed engineering team.
Bachelor’s or master’s degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.
Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency.
Strong experience using AI tools to lead innovation initiatives.
Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering responsible AI adoption across an organization.

Nice To Haves

Backup, disaster recovery, and storage architecture on AWS, including tested cross-region recovery.
Streaming and integration at platform scale using Kafka, Debezium, AWS Database Migration Service, and Spark.
Infrastructure as code and GitOps at platform scale.
Data lifecycle management, including partitioning, archival, and retention for very large databases.
Working knowledge of Java.

Responsibilities

Set the technical direction and long-term roadmap for the Moody’s Insurance Solutions data platform, driving architecture standards and reliability across engineering teams.
Own the reference architecture, including topology, high availability and disaster recovery design, storage layout, tenancy, version strategy, and patch strategy.
Define the platform’s availability contract, including recovery point objective and recovery time objective, and lead drills to validate it.
Own the build-versus-buy position against managed alternatives, including licensing economics, and set operational standards for configuration baselines, drift control, integrity, and maintenance.
Own the security and compliance posture and provide evidence for internal and regulatory review.
Architect the flow of changes from SQL Server into the lakehouse, defining latency, ordering, and schema-evolution guarantees.
Own the lakehouse integration strategy, including table formats, catalog choice and federation, partitioning, and compaction.
Set and sequence the 12-to-24-month platform roadmap against business priorities, identifying risks.
Establish platform paved-road practices, including deployment patterns, schema change management, observability baselines, runbooks, and cost guardrails.
Mentor and sponsor engineers, lead complex problems including during incidents, and represent the platform in architecture forums and to engineering leadership.